Combined Experimental and Numerical Investigation of the ECN Spray G under Different Engine-Like Conditions

Paredi, Davide; Lucchini, Tommaso; D’Errico, Gianluca; Onorati, Angelo; Montanaro, Alessandro; Allocca, Luigi; Ianniello, Roberto

doi:10.4271/2018-01-0281

Cited by 23 publications

(14 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The experimental images showing the liquid phase were obtained using the Mie scattering technique and vapor phase were obtained using schlieren technique. [48][49][50] The Spray-G1 morphology predicted by the simulations shows a good agreement with the experimental spray images. Figure 20 shows the comparison between experimental 18 and computed spray evolution at different time instants after the start of injection for Spray-G2.…”

Section: Spray Simulationssupporting

confidence: 66%

Coupled in-nozzle flow and spray simulation of Engine Combustion Network Spray-G injector

Mohan

Badra

Sim

et al. 2020

International Journal of Engine Research

View full text Add to dashboard Cite

A coupled Eulerian-Lagrangian approach was employed to Engine Combustion Network (ECN) Spray-G simulations. The Eulerian in-nozzle flow simulation was conducted with a small plenum attached to the nozzles, and the results were fed to the Lagrangian spray simulation. For Eulerian simulation, the homogeneous relaxation model (HRM) coupled with the volume of fluid (VOF) method was used. HRM proved to be good at predicting the phase change phenomena due to vaporization mechanisms, that is, both cavitation and flash boiling. As a one-way coupling, quantities such as rate of injection (ROI), mass injected through each hole, discharge coefficient, spray plume angle and half cone angle predicted from the Eulerian simulations were used as the initial and boundary conditions for the subsequent Lagrangian spray simulations using the blob injection model. Non-flashing (Spray-G1) and flashing (Spray-G2) spray was simulated, and the results were validated quantitatively against the published data in terms of the liquid and vapor penetration lengths, and good agreements were obtained. Furthermore, the simulation predicted the liquid and gas axial velocity and sauter mean diameter for Spray-G1 condition in agreement with the droplet size and particle image velocimetry (PIV) measurements from literature.

show abstract

Section: Spray Simulationssupporting

confidence: 66%

Coupled in-nozzle flow and spray simulation of Engine Combustion Network Spray-G injector

Mohan

Badra

Sim

et al. 2020

International Journal of Engine Research

View full text Add to dashboard Cite

show abstract

“…Overall, it is a numerical approach extensively validated during past works in terms of in-cylinder flow, air-fuel mixing and combustion, [21][22][23][24] both for engines and for vessel computational domains. 25,26 The proposed methodology was applied in the context of the Evaporative Gasoline Topic of the ECN6 Workshop and the following conditions were simulated: G1, which is the baseline operating point defined by the ECN for the Spray G injector; G2, which is characterized by flash-boiling fuel evaporation; G3, which is typical of GDI engines early injection events, with very low ambient density; G4 and G7, which are operating points characterized by high ambient density, thus representing late injection events in modern GDI engines.…”

Section: Introductionmentioning

confidence: 99%

“…Overall, it is a numerical approach extensively validated during past works in terms of in-cylinder flow, air–fuel mixing and combustion, 21–24 both for engines and for vessel computational domains. 25,26…”

Section: Introductionmentioning

confidence: 99%

Validation of a comprehensive computational fluid dynamics methodology to predict the direct injection process of gasoline sprays using Spray G experimental data

Paredi

Lucchini

Onorati

et al. 2019

International Journal of Engine Research

Self Cite

View full text Add to dashboard Cite

A detailed prediction of injection and air–fuel mixing is fundamental in modern direct injection, spark-ignition engines to guarantee a stable and efficient combustion process and to minimize pollutant formation. Within this context, computational fluid dynamics simulations nowadays represent a powerful tool to understand the in-cylinder evolution of spray and air–fuel charge. To guarantee the accuracy of the adopted multidimensional spray sub-models, it is mandatory to validate the computed results against available experimental data under well-defined operating conditions. To this end, in this work, the authors proposed the calibration and validation of a comprehensive set of spray sub-models by means of the simulation of the Spray G experiment, available in the context of the engine combustion network. For a suitable validation of the proposed numerical setup in addition to the baseline condition, gasoline direct injection operating points typical of early injection with homogeneous operation, late injection with high ambient density and flash boiling with enhanced fuel evaporation were also simulated. Numerical computations were validated against a wide set of available experimental data by means of an accurate post-processing analysis taking into account axial liquid and vapor penetrations, gas-phase velocity between spray plumes, droplet size, plume liquid velocity, direction and mass distribution. Satisfactory results were achieved with the proposed setup, which is able to predict gasoline spray evolution under different operating conditions.

show abstract

“…To ensure consistency of the results, we set this angle equal to 33 • according to the indications provided in previous studies [31]. Another fundamental parameter is the plume cone angle, which significantly affects the spray evolution [31,32]. Evidence from numerical works available in the literature highlight the absence of a consistent setup for the plume cone angle of the "Spray G" injector [31].…”

Section: Standard Ecn "Spray G" Operating Conditionsmentioning

confidence: 99%

Evaluation of a Scale-Resolving Methodology for the Multidimensional Simulation of GDI Sprays

2019

View full text Add to dashboard Cite

The introduction of new emissions tests in real driving conditions (Real Driving Emissions—RDE) as well as of improved harmonized laboratory tests (World Harmonised Light Vehicle Test Procedure—WLTP) is going to dramatically cut down NOx and particulate matter emissions for new car models that are intended to be fully Euro 6d compliant from 2020 onwards. Due to the technical challenges related to exhaust gases’ aftertreatment in small-size diesel engines, the current powertrain development trend for light passenger cars is shifted towards the application of different degrees of electrification to highly optimized gasoline direct injection (GDI) engines. As such, the importance of reliable multidimensional computational tools for GDI engine optimization is rapidly increasing. In the present paper, we assess a hybrid scale-resolving turbulence modeling technique for GDI fuel spray simulation, based on the Engine Combustion Network “Spray G” standard test case. Aspects such as the comparison with Reynolds-averaged methods and the sensitivity to the spray model parameters are discussed, and strengths and uncertainties of the analyzed hybrid approach are pointed out. The outcomes of this study serve as a basis for the evaluation of scale-resolving turbulence modeling options for the development of next-generation directly injected thermal engines.

show abstract

Combined Experimental and Numerical Investigation of the ECN Spray G under Different Engine-Like Conditions

Cited by 23 publications

References 34 publications

Coupled in-nozzle flow and spray simulation of Engine Combustion Network Spray-G injector

Coupled in-nozzle flow and spray simulation of Engine Combustion Network Spray-G injector

Validation of a comprehensive computational fluid dynamics methodology to predict the direct injection process of gasoline sprays using Spray G experimental data

Evaluation of a Scale-Resolving Methodology for the Multidimensional Simulation of GDI Sprays

Contact Info

Product

Resources

About